For smart grids to develop and be accepted in energy sectors around the world, a number of high risk issues stand in the way of smart grid development. At a macro level these can be placed into three main categories.
1 - Interoperability and standards
Often, key components may not operate together, slowing projects at grid and home level. This could lead to parts of the grid not functioning properly as applications and processes fail to integrate.
For this reason, the National Institute of Standards and Technology (NIST) established the Smart Grid Interoperability Panel (SGIP) to support However the SGIP does not develop the standards but gives stakeholders, including NIST, the opportunity to interact.
This is one of the key failings as the success of the internet as a network is based on rigorous adherence to standards on a global level driven through the IEEE. Which is a body well placed to take on the Smart Grid and it is already doing so with its first smart grids standards see http://smartgrid.ieee.org/ieee-smart-grid
If interoperability is not addressed as critical mass is reached in 2 to 3 years parts of the gird will cease to function reliably as orphan applications and processed are unable to meet up.
Furthermore as grid interconnection increases, standard setting may become too complex for standalone bodies to determine. It would therefore be necessary to involve some computational dimension or Artificial Intelligence to it.
2 - ICT and data management capability
Today’s current Information and communications technology (ICT) and data management technology is struggling to process escalating data volumes, provided by the smart grid. Failure to fix this will not deliver the intelligence and benefits of a Samrt Grid
The smart grid is enabled, through the introduction of many sensors, to record a wide range of data types at a much higher frequency. For example, phasor measurements are likely to be generated at a rate that is 2-3000 times more frequent than now. Home energy readings may be increased by a similar multiple, increasing further as appliance data is introduced.
Real time decisions - Few systems are able to gather and process data from various sources timeously. This may affect the efficiency of data analysis and decision-making. This could pose a problem as many grid actions must be taken by automated systems in real-time.
Interference and inexact data - Smart grid operators must be able to separate “signal” from “noise”, thereby preventing the system from being overloaded by unnecessary data. When there are a number of components operating in close proximity that are communicating using a variety of wireless methods and communications standards, there may be an interference in signals. This could result in the disruption or corruption of data.
Inadequate optimization systems - There appears to be an inadequate understanding of all the systems and their functions, making up the smart grid. As a result, different systems or agents may focus only on individual system parts instead. This approach may not produce the best results across the entire smart grid and its components.
3 - Security
Without an efficient security system, cyber-terrorists can cause major damage to national infrastructure, thereby destroying public support for the smart grid. Despite numerous warnings from the security community, utilities continue to develop the grid in ways that may leave the system exposed to new risks. Sarb Sembhi, chair of the ISACA Security Advisor Group, points out that manufacturers use software that has not been developed with security in mind. He says that these manufacturers tend to believe that as security is not their expertise, security should be implemented at a network level rather than built into the product.
Once energy networks are handed over to ICT, they will become more susceptible to a variety of security threats such as:
- Macro-a terror group threatening to shut down power stations or parts of the national grid
- Micro/”mischievous”-viruses which are designed to switch off home appliances
- Commercial-stealing data on operational performance or harvesting data from thousands of individual users.
Strategic and external factors
In addition to the issues above there are further by and large external factors which also play against the smart grid. The key ones have been identified as:
Unclear business model
Without a clear business model, an uncertainty hangs over the future regulatory regime. There is also confusion as to who must pay for smart metering. This results in key decisions being shelved, sometimes indefinitely.
Unclear communication standards
Utilities are adopting a “wait and see” approach due to the lack of clarity over best communication standards. As a result, grid infrastructure investment has slowed.
Perceived data security
Consumers are reluctant to support smart grid deployment due to security concerns.
Pending regulatory response to core issues
Before expanding their business further, utilities wait for regulators to make decisions on core issues such as payment for smart meters and wholesale electric prices.
Lack of funds
Due to a shortage in federal funding, many projects in the US are seeing delays or are being abandoned altogether.
The transformation to the smarter grid is in full swing driven by powerful accelerators. Significant investments around the world are being made in smart meter implementation. However, many obstacles have yet to be resolved in order to avoid a growing uncertainty around the benefits that the smart grid has to offer. These may have a negative effect on the smart grid’s long term success if not dealt with in time and at a faster pace.